Senior Software Engineer

Software Engineer, AI & Automation — Corrigo Platform P3 (Senior) | #JLLTechAmbitions About The Role JLL is a leading professional services firm that specializes in real estate and investment management. Our vision is to reimagine the world of real estate, creating rewarding opportunities and amazing spaces where people can achieve their ambitions. In doing so, we will build a better tomorrow for our clients, our people, and our communities.

JLL Technologies is a specialized group within JLL. At JLL Technologies, our mission is to bring technology innovation to commercial real estate. We deliver unparalleled digital advisory, implementation, and services solutions to organizations globally. Our goal is to leverage technology to increase the value and liquidity of the world’s buildings, while enhancing the productivity and happiness of those that occupy them.

What This Job Involves We’re looking for a Software Engineer to help build the next generation of the Corrigo Platform — one where AI agents and automation are core to the product, not an add-on. Corrigo delivers a single, powerful CMMS uniting operations, asset & work order management, maintenance, and analytics to deliver smarter facilities management. Corrigo is one of the leading CMMS enterprise solutions in the world, with a client base of about 4 million users across more than 2 million locations and hundreds of millions of connected assets.

This is a hybrid role: you’ll build and ship core platform features alongside the rest of the engineering team, and you’ll design and build AI agents and automated workflows that extend Corrigo’s capabilities — from intelligent work order triage to autonomous maintenance recommendations. The ideal candidate is a strong software engineer first, with hands-on experience building applications powered by LLMs and a fluency in using AI coding tools to move faster without sacrificing quality.

As a Software Engineer at JLL Technologies, you will:

• Work closely with the Product Management team to understand product requirements and translate them into executable engineering tasks
• Develop new features, enhance existing features, and optimize functionality across the Corrigo platform, from design through testing and deployment
• Design, build, and productionize AI agents and LLM-powered workflows (e.g., work order triage, intelligent routing, natural-language search, automated diagnostics) that extend Corrigo’s core CMMS capabilities
• Integrate agentic and automation capabilities with existing services, APIs, and data pipelines, with attention to reliability, cost, latency, and safety of AI-driven decisions
• Evaluate, prototype, and adopt AI coding tools and agentic development workflows (code generation, AI-assisted testing, automated code review) to accelerate the team’s delivery
• Support the customer service team in addressing escalated issues across a variety of areas
• Write clean, high-quality, maintainable code, and build evaluation/test harnesses for AI-driven features
• Participate in code reviews — both submitting your own work and reviewing peers’ code, including AI-generated or AI-assisted code
• Troubleshoot and independently resolve complex issues within your domain, including issues specific to AI agent behavior and model outputs
• Contribute to team knowledge sharing on AI engineering practices, prompt design, and agentic architecture patterns

Sounds Like You? What We Are Looking For Critical Skills

• At least a bachelor’s degree in Computer Science or a related field
• 6+ years of professional experience developing SaaS/PaaS products, including recent hands-on work building AI-powered or LLM-integrated features
• Expertise in at least one of frontend or backend development
• Practical experience building with LLMs — prompt engineering, retrieval-augmented generation (RAG), function/tool calling, or agentic frameworks (e.g., LangChain, LangGraph, Semantic Kernel, or equivalent)
• Hands-on, daily use of AI coding tools (e.g., GitHub Copilot, Cursor, Claude Code, or similar) for code generation, refactoring, code review, and automated testing — with the ability to critically evaluate and validate AI-generated output
• Ability to design AI agent workflows that are observable, testable, and safe to operate in production, including guardrails for model errors or unexpected behavior
• Understanding of business requirements, with the ability to translate them …